The San Luis Valley (SLV) Health and Aging Study is the only rural, population-based cohort study of Hispanic and non-Hispanic white (NHW) aging-related issues in the United States. This study has collected both prevalence and incidence data related to the distribution, causes and consequences of disability and functional limitation in a biethnic population of elderly living in a rural Colorado setting. The focus of the proposed study is to further investigate Hispanic and NHW contrasts in disability incidence in a population where access to medical care is not a confounding factor. The SLV Health and Aging Study was established in 1992 and has included detailed assessments on 1433 participants who comprise a representative sample of both community dwelling and area nursing home residents. The prevalence data from this population suggest intriguing differences between Hispanic and NHW elderly with regard to activities of daily living, instrumental activities of daily living, cognitive functioning and stated perceived quality of life. The first follow-up examination was completed June 1997 with a 92% response rate. These incidence data are less biased by mortality and duration of endpoints, and will allow description of temporal relationships among variables of interest. There is an expectation that continued assessment of this unique cohort will permit it to serve as a core population laboratory for further studies of minority aging and to conduct analyses of these data before deciding if more detailed follow-up of this cohort is warranted. The proposed study includes: 1) conducting ongoing surveillance of the cohort in order to update contact information, determine vital status and causes of death, and assess self-reported physical function; and 2) analysis of new incidence data to determine the development of and changes in functional impairment, depression, cognitive impairment, changes in executive function and perceived quality of life. These analyses will focus on examining important ethnic differences, developing analytic models to explore multiple pathways to disability, and identification of predictors of disability and mortality to develop prevention strategies.